How Fast Are We? Throughput Times for Admissions from the Emergency Department

1. How Fast Are We? Throughput Times for Admissions from the Emergency Department Brian Hom; Deborah Porter RN, NM; Kathleen Chambers RN, MSN, CPN; Laura Gaertner RN, BSN Cleveland Clinic Data Background Overcrowding and inefficient patient throughput is a major problem throughout hospitals in the United States. The Joint Commission (TJC) and the Center for Medicaid and Medicare Services (CMS), which govern and evaluate healthcare organizations such as the Cleveland Clinic, are aware of the ongoing patient throughput problems and know it needs to be improved. However, there is no one right way to solve the issue since each hospital has its own unique factors that affect patient throughput. Long patient waiting times result in slow throughput, thus jeopardizing the ability for hospitals to provide the best patient care they possibly can. Conclusions • The purpose of this study is to develop a base that can be used for further research in the improvement of patient throughput • Improving patient throughput or flow will improve patient care and satisfaction • This data will help the hospital and staff gain insight as to what can be done to improve patient throughput • Many factors that affect patient throughput are out of the hospital and staff’s control (i.e. IV contrast fluid requires several hours before certain tests can be done) • Improving patient throughput is important because it directly affects patient care, hospital revenues, and overall satisfaction of the patients and staff • A hospital functions as one team and all the departments need to work together in order to resolve the patient throughput issue Results Hypothesis • Figure 1 shows the average time for each shift from when a patient arrives in the ED to when he/she gets admitted • Figure 2 shows average time from disposition to when the bed is ready. Times are often longer in the morning because patients need to wait for the inpatient beds to be discharged. • According to figure 3, there is more often a longer time between when the bed is ready and when the report is called in the evening. • Figure 4 shows that the longest times between when the report was called and when patients go up to the floor from the ED occurs in the day and evening. • Figure 5 shows the trend of the length of the total process for each shift • The Emergency Room generally receives more patients in the evening than the other shifts, resulting in longer waiting times and time between “checkpoints” • A base has been developed and can lead to further research as to what may improve the throughput situation and when it lags the most. • Based on the data, the biggest throughput factor seems to be the diagnosis, treatment, tests, and registration before a patient is finally admitted • Other major factors that may affect throughput: • Not enough staff • Competition for inpatient beds with scheduled admissions • Emergency patients tend to be older and have more complex conditions-- more tests and treatments are performed since the standard for admittance and medical practices are changing • Inability to transfer emergency patients to inpatient beds If data is collected about the average time taken between key steps in the patient throughput process (arrival, disposition, bed ready, report, and going up) in the adult emergency room, then a baseline will be developed that can lead to future research on possible improvements to the patient throughput process and the staff can focus on improving the specific areas that may slow down patient throughput times. Methodology Recommendations A retrospective study was conducted on the throughput times of adult patients admitted normally (no cardiac arrest or stroke) from Fairview Hospital’s Emergency Department. Using the Cleveland Clinic’s Epic System, charts of approximately 300 random patients that were admitted to the hospital from the Emergency Department were looked at to see the time elapsed between certain points in the throughput process. The charts of ten admitted patients from each day between June 12, 2011 to July 4, 2011 were utilized. The patients were chosen at random and were categorized by when they were admitted to the floor: day shift (7 am to 3 pm), evening shift (3 pm to 11 pm), and night shift (11 pm to 7 am). The arrival time, disposition time, assignment or bed ready time, report time, and time the patient went to the unit was recorded for each patient. The amount of time, in minutes, were calculated between each checkpoint. The average times for each shift in each day were calculated and compared. Also, opinions from staff in various departments were gathered on why there is a patient throughput and overcrowding problem and what can be done to improve it. • Create a “dock and triage” system for the emergency department, where a physician is stationed in the triage and can quickly treat certain patients • Test the effects of a designated area for inpatient beds ready to be discharged because many patients wait for hours just for their doctors to make rounds and tell them they can be discharged • Increase the capacity of the hospital • Perform further research that tests different ideas that improve efficiency and throughput • Use a larger data set to get more accurate results • In future studies, make comparisons to other area hospitals Works Cited “Emergency Department Crowding-Patient Flow/‌Throughput.” Emergency Nurses Association. N.p., 2011. Web. 22 June 2011. <http://www.ena.org/‌IQSIP/‌ENAStrategicPriorities/‌Crowding Patient%20Flow/‌Pages/‌Default.aspx>. Handel, Daniel A, MD, et al. “Emergency Department Throughput, Crowding, amd Financial Outcomes For Hospitals .” Wiley Online Library. N.p., 2011. Web. 19 July 2011. <http://onlinelibrary.wiley.com/‌doi/‌10.1111/‌j.1553-2712.2010.00814.x/‌full>. Joelving, Frederick. “ER crowding tied to higher death rates.” Reuters. N.p., 13 June 2011. Web. 28 June 2011. <http://www.reuters.com/‌article/‌2011/‌06/‌13/‌us-er-crowding- idUSTRE75C0Q220110613>. “Patient Throughput.” Hospitals in Pursuit of Excellence. N.p., 2010. Web. 22 June 2011. <http://www.hpoe.org/‌topic-areas/‌patient-throughput.shtml>.